• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.2
• /
• pp.579-603
• /
• 2018

In this paper we propose a QoS-enhanced intelligent stochastic optimal fair real-time packet scheduler, QUEST, for 4G LTE traffic in routers. The objective of this research is to maximize the system QoS subject to the constraint that the processor utilization is kept nearly at 100 percent. The QUEST has following unique advantages. First, it solves the challenging problem of starvation for low priority process - buffered streaming video and TCP based; second, it solves the major bottleneck of the scheduler Earliest Deadline First's failure at heavy loads. Finally, QUEST offers the benefit of arbitrarily pre-programming the process utilization ratio.Three classes of multimedia 4G LTE QCI traffic, conversational voice, live streaming video, buffered streaming video and TCP based applications have been considered. We analyse two most important QoS metrics, packet loss rate (PLR) and mean waiting time. All claims are supported by discrete event and Monte Carlo simulations. The simulation results show that the QUEST scheduler outperforms current state-of-the-art benchmark schedulers. The proposed scheduler offers 37 percent improvement in PLR and 23 percent improvement in mean waiting time over the best competing current scheduler Accuracy-aware EDF.

• Journal of Technology Innovation
• /
• v.12 no.1
• /
• pp.67-114
• /
• 2004

This study attempts to integrate causal model with competitiveness evaluation model, both of which have developed independently of each other, in connection with many studies on PMES (performance measurement and evaluation system) including the BSC (balanced scorecard) of Kaplan and Norton (1992, 1996). For this attempt, this study is composed of four analyses : First, this study develops a structural model for evaluating and diagnosing corporate ‘comprehensive’ competitiveness including quality competitiveness, derive CCI (comprehensive competitiveness index) and QCI (quality competitiveness index) ; Second, this study analyzes the determinants of quality competitiveness, the impacts of quality competitiveness, on product design and product reliability, and the impacts of product design and product reliability on quality competitiveness in the comprehensive competitiveness evaluation model of this study. Third, this study empirically identifies the positioning of product design in the quality competitiveness evaluation model of this study and the functional relationship between product design and other functions : product development, manufacturing, marketing, and marketing, and sales in the same comprehensive competitiveness evaluation model, estimate the determinants of product design and its impacts, thereby providing some empirical findings for the foundation of design management theory, and Fourth, this study identifies the positioning of product reliability in the same quality competitiveness evaluation model, estimate the reliability function and the functional relationship between product reliability and other dimensions of product quality, and tests the hypotheses on the causality of product reliability.

• Korean Management Science Review
• /
• v.30 no.2
• /
• pp.43-61
• /
• 2013

With the recent introduction of supply chain management (SCM), quality management has extended from within companies to between companies. As a result, supply chain quality management (SCQM) has received increased attention. However, existing SCQM studies only focus on what impact quality control in supply chains have on company performance while virtually no studies examine quality control efficiencies. This paper, therefore, evaluated the SCQM efficiency of a parent company and its partner companies by using Data Envelopment Analysis (DEA) based on the Quality Collaboration Index for Supply Chain Management (QCI-SCM) conducted by the Korean Standards Association for its 'Quality Innovation-Based Building and Expansion of Business.' Study results showed that a parent company and its partners showed an overall average efficiency of approximately 80% (parent company 80.37%, partner company 79.05%). By also performing a discriminant analysis based on the calculated efficiency scores using DEA, factors that made companies efficient or inefficient were different between the two groups. In parent companies, efficiency and inefficiency were determined by factors such as communication, infra-structure, support, delivery of quality, and benefit sharing, whereas in partner companies, talent development, infrastructure, crisis management, and delivery of quality were the determining factors. In this paper, we examined the efficiency of SCQM and analyzed them from the perspective of both the parent company and partner companies to offer strategic SCQM insights.